Room Management Research Articles

Smart Meeting Room Access Control and Management Via IOT

In Most Meeting Room Scheduling or Management System, The Availability of Meeting Rooms Are Mainly Based on Pre-Determined Schedules. However, Since the Meeting Duration Is Not Always Exact as It Is Scheduled, There Are Some Situations That A Meeting Room Is Underutilized. Therefore, In This Paper, We Present A Smart Meeting Room Scheduling and Management System Which Detect Occupancy Status of Meeting Rooms in Real Time and Integrate This Information into The Scheduling Application to Support Meetings and Increase Room Utilization. Occupancy Data Is Sent to A Central Application Server by UDP Over Ip Protocols. On This Server, A Web Application Is Developed and Hosted to Not Only Allow People Book Rooms for Their Meetings, But Also Check the Utilization of These Rooms Based on Predefined Policies. The System Also Supports Meetings by Providing Real-Time Availability of Meeting Rooms to Users.

INOVASI IOT UNTUK PENGELOLAAN DAN KEAMANAN RUANG ARSIP: IMPLEMENTASI ESP32 DENGAN SENSOR API DAN SUHU DHT11

This study aims to design and develop a prototype IoT-based archive room monitoring system to enhance security and efficiency in archive management at the Village Office of Desa Pingit, Pringsurat District, Temanggung Regency. The system utilizes a UV Flame Detector for fire detection and a DHT11 sensor for monitoring temperature and humidity, with an ESP32 as the main controller connected via Wi-Fi. Integrated with the Telegram app, users can receive real-time notifications and updates on archive room conditions, facilitating remote monitoring. Testing results indicate that the system effectively detects fire presence and accurately provides temperature and humidity updates. This innovation is expected to aid in risk management and archive protection, offering a practical solution for modern archive room management.

Development of an estimation formula for preparation time of anesthesia induction and surgery accounting for clinical department factors in optimal surgery schedule management

Efficient operating room management is essential and requires precise surgery scheduling. We hypothesized that an estimation formula for the preparation time for anesthesia induction and surgery could be developed by incorporating anesthesia and surgical factors, as well as the ‘clinical department,’ into the formula. This retrospective observational study analyzed 12,528 scheduled surgical cases. A regression analysis that included the clinical department, six anesthesia factors, and five surgical factors was conducted. This analysis aimed to develop both an analytical framework and an equation for estimating the time required for both anesthesia induction and surgical preparation. Our estimation formula wielded high accuracy (R2 = 0.801). Particularly, there was only a difference of less than 3 min for surgeries under general anesthesia. In addition, modeling preparation time using “medical interventions performed in the operating room” as a factor instead of patient characteristics was found to be beneficial. It was possible to develop a highly accurate formula for estimating preparation time of anesthesia induction and surgery by analyzing the anesthesia factors and the surgical factors and incorporating the clinical department as an estimation factor. However, this study represents the development phase of the estimation formula. A multicenter study is essential to validate its generalizability and robustness across different settings before broader application.

A tactical carcass optimisation tool for assisting boning room managers to increase boning room profit

In collaboration with Australian lamb supply chains, an integer linear programming model was developed for use by processors to optimally allocate carcasses to different cutting plans for implementation in a boning room on a daily or lot basis. This tactical carcass optimisation tool (TCOT) addresses the daily challenge of developing operational plans to process carcasses into products whilst maximising profitability subject to constraints on carcass availability, variability of carcass weight and fatness, number of product orders, product size and retail prices. Predicted weights for all available products were derived from cut-weight prediction algorithms established from the combination of carcass weight and fatness ranges. Carcass fatness was expressed as lean meat yield percentage (LMY%) and measured using dual-energy X-ray absorptiometry (DXA) of hot carcasses immediately after slaughter. The TCOT utilises a group-based labour cost model which closely aligns with real-world supply chain practices. The function and application of the optimisation tool were tested in two contrasting case studies. The first case study demonstrated the ability of the optimiser to allocate carcasses to optimal cutting plans based on carcass weight and LMY%. The second case study examined the potential value of the tool for processors supplying lamb into the Australian domestic lamb market and subject to the constraints applied, demonstrated opportunities to increase profitability by at least 1 % compared to current best practice. This work provides a pathway whereby objective carcass measurement technology, combined with carcass sortation and optimisation algorithms, can be leveraged to improve profitability for lamb supply chains.

Method of cooling server rooms

Objective. In today's world, where the amount of data is growing every day, the importance of reliable and efficient data centers (DPCs) is becoming increasingly clear. One of the key aspects of maintaining data center availability and reliability is ensuring adequate cooling of server rooms. This scientific work is devoted to the study and analysis of various cooling techniques used in server rooms. Method. The study is based on thermodynamic analysis methods to optimize cooling systems to improve their efficiency and reduce energy consumption. Result. The work examines both traditional cooling systems and modern innovative solutions that improve cooling efficiency while reducing energy consumption. The authors compare different cooling methods, evaluate their advantages and disadvantages, and analyze the potential economic and environmental benefits of introducing advanced technologies into server room management practices. Conclusion. The choice of the optimal cooling method should take into account the specifics of the server equipment, thermal loads, room size and other factors. It is also important to pay attention to maintenance and selection of the optimal cooling system in accordance with the needs and characteristics of the server equipment.

Delivery Room Management of Infants with Surgical Conditions.

Delivery room resuscitation of infants with surgical conditions can be complex and depends on an experienced and cohesive multidisciplinary team whose performance is more important than that of any individual team member. Existing resuscitation algorithms were not developed for infants with congenital anomalies, and delivery room resuscitation is largely dictated by expert opinion extrapolating physiologic expectations from infants without anomalies. As prenatal diagnosis rates improve, there is an increased ability to plan for the unique delivery room needs of infants with surgical conditions. In this review, we share expert opinion, including our center's delivery room management for neonatal noncardiac surgical conditions, and highlight knowledge gaps and the need for further studies and evidence-based practice to be incorporated into the delivery room care of infants with surgical conditions. Future research in this area is essential to move from an expert-based approach to a data-driven approach to improve and individualize delivery room resuscitation of infants with surgical conditions.

Retrospective analysis of the resuscitation room management of nontraumatic critically ill children in a university emergency department (OBSERvE-DUS-PED study)

The establishment of a resuscitation room management for nontraumatic critically ill children appears to make sense. This study collected data of pediatric patients suffering from nontraumatic critically ill conditions treated in aresuscitation room. The retrospective OBSERvE-DUS-PED study (November 2019-October 2022) recorded pediatric patients (age < 18years) who were admitted to the emergency department (ED) for resuscitation room care. The routinely documented data on treatment were taken from the hospital information system MEDICO® and the patient data management system COPRA® in accordance with the OBSERvE dataset. The study was approved by the Ethics Committee of the Medical Faculty of the Heinrich Heine University (2023-2377). The study included 52pediatric resuscitation room patients. Adolescents aged 14-17years were the most frequent in the cohort representing 37% of the total and neonates/infants (0-1year) were lowest at 8%. The most common symptoms categorized according to ABCDE problems were disturbance of consciousness(D) at 61%, cardiovascular failure(C) at 25%, respiratory insufficiency(B) at 6%, airway obstruction(A) and exposure/environment (E) problems each at 4%. The out-of-hospital and in-hospital emergency procedures were performed with the following frequencies: venous (58%vs. 65%), intraosseous (14%vs. 2%) and central venous access (0%vs. 12%), invasive airway management (35% vs.8%), cardiopulmonary resuscitation (21%vs. 10%), vasopressors (15%vs. 17%), and intra-arterial pressure measurement (0%vs. 17%). The mean duration of resuscitation room management was 70 ± 43 min. The 30-day mortality was 17%. The OBSERvE-DUS-PED study demonstrates the major challenges in the care of critically ill nontraumatic pediatric patients, both in out-of-hospital and in-hospital management. The variety and complexity of the referral diagnoses as well as the immediate vital threat to the patients make it appear sensible to treat such patients primarily in aresuscitation room of the ED due to the available material, infrastructural and personnel resources.

Lessons in Manufacturing Efficiency: 12 by 12

In “Lessons in Manufacturing Efficiency: 12 by 12,” we explore how manufacturing efficiency principles can revolutionize operating room (OR) management. By addressing inefficiencies and adopting strategies like throughput accounting and the Theory of Constraints, this paper proposes a model for enhancing OR throughput, quality of care, and patient outcomes. Emphasizing technology integration and systematic process improvement, we offer a comprehensive framework for transforming surgical services into highly efficient, patient-centered operations, thereby setting a new standard for healthcare delivery.

Integrated operating room planning and scheduling: an ILP-Based off-line approach for emergency responsiveness at a local hospital in Naples

This paper addresses a real-world Integrated Operating Room Planning and Scheduling (IORPS) problem encountered by a local hospital in Naples, characterized by stringent emergency management constraints, requiring treatment initiation within a 20-minute time-window. We tackle this problem by an original Integer Linear Programming formulation, capable of dealing with different operating room management strategies (open, block and block-modified). Our work differs from conventional cost-focused models by adopting a patient-oriented objective function, aligning with public hospitals obligations. The proposed method has been validated using real-world data provided by the hospital. The performed experimentation demonstrates the efficiency of the approach, capable of determining the optimal solution within an acceptable computation time that aligns with hospital requirements. Moreover, it also highlights the relevance of using our optimization approach to reduce delays in emergency responsiveness. This confirms its practical usage as a substitute for the current manual procedure.

Bibliometric Research on Surgical Scheduling Management from the Perspective of Web of Science.

Reasonable surgical scheduling management is crucial to optimize the utilization rate of operating room. This study aims to understand the context, frontier and hot spots of surgical scheduling management research, in order to provide reference for surgical scheduling optimization. Literature on operation scheduling management collected in Web of Science core collection database was searched from the database establishment to June 21, 2023. HisCite Pro 2.1 software was used to analyze the publication time, countries, research institutions, journals, authors, keywords and highly cited papers. A total of 1383 literatures were included, and research institutions in the United States, Canada and other countries played a leading role in this field. Among them, the combination of machine algorithm and system model optimization to improve the accuracy of surgical duration prediction is the future research focus in this field. Improving operation efficiency is one of the key issues in operating room management. Managers should find the best operation scheduling plan from a more detailed and comprehensive perspective to improve operation efficiency.

Artificial Intelligence Applications for Thoracic Surgeons: "The Phenomenal Cosmic Powers of the Magic Lamp".

In the digital age, artificial intelligence (AI) is emerging as a transformative force in various sectors, including medicine. This article explores the potential of AI, which is akin to the magical genie of Aladdin's lamp, particularly within thoracic surgery and lung cancer management. It examines AI applications like machine learning and deep learning in achieving more precise diagnoses, preoperative risk assessment, and improved surgical outcomes. The challenges and advancements in AI integration, especially in computer vision and multi-modal models, are discussed alongside their impact on robotic surgery and operating room management. Despite its transformative potential, implementing AI in medicine faces challenges regarding data scarcity, interpretability issues, and ethical concerns. Collaboration between AI and medical communities is essential to address these challenges and unlock the full potential of AI in revolutionizing clinical practice. This article underscores the importance of further research and interdisciplinary collaboration to ensure the safe and effective deployment of AI in real-world clinical settings.

Development of a checklist framework for kidney transplantation.

Kidney transplantation is the therapy of choice for end-stage kidney disease, and a fast-growing transplant procedure worldwide. Diverse clinical practices for recipients and donors' selection and management between transplant centers hinder the creation and dissemination of an anesthesia-surgical checklist. Components of the anesthesia-surgical checklist were selected after a review of the English literature using PubMed search for donor, recipient and graft protocols and outcomes of existing practices in the field of kidney transplantation. Key elements of the most relevant articles were combined with our own center's experience and formulated into the proposed checklist. The checklist is intended to be used perioperatively, once patient receives an offer. The perioperative checklist centers primarily on the following donor and recipient's factors: (i) Review of the pretransplant candidate workup; (ii) Assessment of donor/graft status; (iii) Hypothermic machine perfusion parameters; (iv) Operating room management; (v) Sign out. The proposed kidney transplant checklist was designed to ensure consistency and completeness of diverse tasks and facilitates team communication and coordination. We present a novel standardized combined anesthesia-surgical checklist framework for kidney transplant aimed at increasing perioperative safety and streamline the perioperative care of recipients. Future validation studies will determine its clinical feasibility and post-implementation efficacy.

Delivery room and early postnatal management of neonates with congenital heart disease.

Advancements in prenatal detection have improved postnatal outcomes for patients with congenital heart disease (CHD). Detailed diagnosis during pregnancy allows for preparation for the delivery and immediate postnatal care for the newborns with CHD. Most CHDs do not result in hemodynamic instability at the time of birth and can be stabilized following the guidelines of the neonatal resuscitation program (NRP). Critical CHD that requires intervention immediately after birth is recommended to be delivered in facilities where immediate neonatal and cardiology care can be provided. Postnatal stabilization and resuscitation for these defects warrant deviation from the standardized NRP. For neonatal providers, knowing the diagnosis of fetal CHD allows for preparation for the anticipated instability in the delivery room. Prenatal detection fosters collaboration between fetal cardiology, cardiology specialists, obstetrics, and neonatology, improving outcomes for neonates with critical CHD.

Huge urgency and consummate skill: an interview with Jim Pennington

ABSTRACT Jim Pennington is a printer and small press publisher who trained at London's North-Western Polytechnic and the London College of Printing. Over the course of his long career, he has worked as a print room and production manager first for the British Safety Council (1971–75) then for the anti-poverty charity War on Want (1975–79) and then for the Lithosphere Printing Co-operative (1979–1991), among others. In parallel, Pennington ran Aloes Books, the influential small press he established with the poets Allen Fisher and Dique Miller. Aloes Books has published key works by Kathy Acker, Thomas Pynchon and William Burroughs, among many others.

Scaling performance frontiers across multiple perioperative services

BackgroundOne of the primary principles governing operating room management includes maximizing clinical efficiency and optimizing the time used in the high-cost, high-revenue environments represented by operating rooms. Under-utilized and over-utilized times are elementary metrics that describe the operating room performance. Performance frontiers, the graphical representation of a hypothetical maximum performance of a manufacturing unit given a set of operating choices, visualize the maximal efficiency of systems and their existing constraints. MethodsMonthly aggregated operating room metrics from services at the University of Vermont Medical Center (UVM), Stanford Hospital, and the University of Alabama (UAB) at Birmingham Hospital were extracted. Paired under- and over-utilized times were plotted against each other. Performance frontiers representing the optimal performance of each service were overlaid. ResultsThe Kolmogorov-Smirnov test for goodness-of-fit at 95 % level of significance confirms that the performance frontiers representing UVM and Stanford (K-S = 0.9507, p < 0.0001), UVM and UAB (K-S = 0.9989, p < 0.0001), and Stanford and UAB (K-S = 0.9773, p < 0.0001), indicating each service is represented by a different performance frontier. ConclusionsOur analysis shows that the performance frontier defining the optimal efficiency of UVM is more efficient than that of Stanford and UAB. Differences in efficiency may be the result of a collection of factors that must be the subject of future research, including but not limited to organizational differences limited in scale of institutions. Choices in operating room management must be made in relation to the existing organizational structures of each institution and their specific capacity to make changes in tactical decisions. Systemic interventions should be implemented via qualitative analysis of more efficient services, defined by the relative positioning of relevant performance frontiers.

At the threshold of viability: to resuscitate or not to resuscitate – the perspectives of Israeli neonatologists

ObjectiveThis study aims to examine the perspectives of neonatologists in Israel regarding resuscitation of preterm infants born at 22–24 weeks gestation and their consideration of parental preferences. The factors that...

Retraction Note: RFID tag recognition model for Internet of Things for training room management

This article has been retracted. Please see the Retraction Notice for more detail: https://doi.org/10.1186/s13635-024-00154-7

Nurses’ perceptions of discharge planning implementation: A descriptive qualitative study

Background: Discharge planning is crucial in hospitals to ensure continuous patient care, thereby preventing re-admissions or complications. However, its implementation still requires improvement due to various obstacles and variances in nurses’ perceptions. Objective: This research aims to explore nurses’ perceptions regarding the implementation of discharge planning. Methods: This study is a descriptive qualitative research involving 14 participants selected through purposive random sampling. Data was collected from April to June 2023 through in-depth interviews, with notes taken and recordings made for transcription. Data analysis was conducted using the Colaizzi method. Results: Participants exhibited a good understanding of discharge planning, yet disparities emerged in their perceptions regarding ten key themes: knowledge, goals, and benefits; organizational aspects in implementation management; activity mechanisms; methods and media employed; implementation steps/flow; implementation content; particularly notable was the theme of implementation timing; evaluation processes in implementation; availability of specialized formats and documentation procedures/format completion; and encountered implementation categories and room-related obstacles. These themes emerged as significant areas needing attention based on the research findings. Conclusion: Nurses’ perceptions regarding the implementation of discharge planning have not been optimized due to constraints imposed by hospital management policies and room management, differences in nurses’ perceptions and attitudes towards implementation, and factors related to patients and their families.

SURVEY ON THE IMPLEMENTATION OF HEALTH EDUCATION BY NURSES IN THE INPATIENT ROOM OF TYPE B HOSPITAL

A nurse is a professional who can provide care to individuals, families, groups, or communities, both in sickness and health. One of the important tasks of nurses is as educators. Health education is a form of education that aims to change the behavior of individuals, groups and communities so that they can improve their health independently. The purpose of this study was to analyze the implementation of the role of nurses as providers of health education to patients. This study used a descriptive survey design. The research sample used a total sampling technique of 18 respondents consisting of nurses who served in the inpatient room of a type B hospital. The measuring instrument used an instrument in the form of a Nurse's Education Patient Questionnaire (NEPQ). Data analysis using exploratory descriptive. The results obtained 67% of nurses in the good category on the values and knowledge of nurses, 50% in the good category on the environment for providing health education, 61% in the good category on the organization of health services, 61% in the good category on interdisciplinary and peer cooperation, 61% in the good category on activities providing health education. Supporting factors for nurses as educators include the existence of a PKRS team and clear documentation related to health education documentation. While the inhibiting factors include the lack of support from the room manager and the lack of availability of nurses' time. Nurses are expected to further improve the responsiveness dimension and hospital management to increase support or encouragement, especially holding socialization/workshops and encouraging health education providers by nurses to get training, routine scheduling, and supervision to optimize the provision of health education.

Attitudes of Jordanian Anesthesiologists and Anesthesia Residents towards Artificial Intelligence: A Cross-Sectional Study.

Success in integrating artificial intelligence (AI) in anesthesia depends on collaboration with anesthesiologists, respecting their expertise, and understanding their opinions. The aim of this study was to illustrate the confidence in AI integration in perioperative anesthetic care among Jordanian anesthesiologists and anesthesia residents working at tertiary teaching hospitals. This cross-sectional study was conducted via self-administered online questionnaire and includes 118 responses from 44 anesthesiologists and 74 anesthesia residents. We used a five-point Likert scale to investigate the confidence in AI's role in different aspects of the perioperative period. A significant difference was found between anesthesiologists and anesthesia residents in confidence in the role of AI in operating room logistics and management, with an average score of 3.6 ± 1.3 among residents compared to 2.9 ± 1.4 among specialists (p = 0.012). The role of AI in event prediction under anesthesia scored 3.5 ± 1.4 among residents compared to 2.9 ± 1.4 among specialists (p = 0.032) and the role of AI in decision-making in anesthetic complications 3.3 ± 1.4 among residents and 2.8 ± 1.4 among specialists (p = 0.034). Also, 65 (55.1%) were concerned that the integration of AI will lead to less human-human interaction, while 81 (68.6%) believed that AI-based technology will lead to more adherence to guidelines. In conclusion, AI has the potential to be a revolutionary tool in anesthesia, and hesitancy towards increased dependency on this technology is decreasing with newer generations of practitioners.